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    Numerical Methods and Optimization in Finance

    Numerical Methods and Optimization in Finance

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    Bog E-bog
    • Format
    • Bog, hardback
    • Engelsk

    Beskrivelse

    This book describes computational finance tools. It covers fundamental numerical analysis and computational techniques, such as option pricing, and gives special attention to simulation and optimization. Many chapters are organized as case studies around portfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.

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    Detaljer
    • SprogEngelsk
    • Sidetal600
    • Udgivelsesdato25-08-2011
    • ISBN139780123756626
    • Forlag Academic Press Inc
    • FormatHardback
    Størrelse og vægt
  • Vægt910 g
    • coffee cup img
    10 cm
    book img
    15,2 cm
    22,9 cm

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    Finance Experimental design Finite differences Computer arithmetic Greeks Extreme value theory Copula Numerical integration Mathematical methods OPTIMIZATION Sparse matrices Arma Differential evolution Nonlinear Least Squares Algorithmic complexity Boundary conditions Constraints Brownian bridge Quadratic programming Threshold Accepting Financial Optimization Jacobi method Value-at-risk Robust regression Steepest Descent Interest Rate Models Sor Direct methods Iterative methods Bootstrap Downside Risk Model risk Markov chain Geometric Brownian Motion Numerical methods in finance Approximation Pseudo-random numbers GARCH Implied volatility American option Option pricing Condition number Term structure models Particle swarm optimization Matrix Factorization Heston model Agent-based modeling ^ Random number generator Portfolio Optimization Nelson-Siegel model Local search Newton method Characteristic function Portfolios Financial Modeling Model evaluation Optimization heuristics Unconstrained optimization Direct Search Barrier Option Volatility Clustering (auto)regression Fixed-point Adaptive Expectations Binomial Trees Asset selection Calibration of option pricing models Bates Model Box-Muller method Constant proportion portfolio insurance (CPPI) bisection Early Exercise Boundary Escrowed dividend model Explicit method Early Exercise Gauss-Newton Gauss rules Crank-Nicolson Gap risk historical simulation Implicit method θ-method initial conditions Least Squares problems inversion method Least Trimmed Squares Levenberg-Marquardt Linear correlation Model accuracy Nelder-Mead direct search Metropolis algorithm Numerical instability Nelson-Siegel-Svensson model Gauss-Seidel method Rank Correlation root finding Risk-reward measures Machine precision Wiener processes Moving average processes Least Median of Squares Operation Count

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